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The Big Thaw

Tim Appenzeller, National Geographic
From Greenland to Antarctica, the world is losing its ice faster than anyone thought possible. Can humans slow the melting?
…From the high mountains to the vast polar ice sheets, the world is losing its ice faster than anyone thought possible. Even scientists who had monitored Chacaltaya since 1991 thought it would hold out for a few more years. It’s no surprise that glaciers are melting as emissions from cars and industry warm the climate. But lately, the ice loss has outstripped the upward creep of global temperatures.

Scientists are finding that glaciers and ice sheets are surprisingly touchy. Instead of melting steadily, like an ice cube on a summer day, they are prone to feedbacks, when melting begets more melting and the ice shrinks precipitously. At Chacaltaya, for instance, the shrinking glacier exposed dark rocks, which sped up its demise by soaking up heat from the sun. Other feedbacks are shriveling bigger mountain glaciers ahead of schedule and sending polar ice sheets slipping into the ocean.

Most glaciers in the Alps could be gone by the end of the century, Glacier National Park’s namesake ice by 2030. The small glaciers sprinkled through the Andes and Himalaya have a few more decades at best. And the prognosis for the massive ice sheets covering Greenland and Antarctica? No one knows, if only because the turn for the worse has been so sudden. Eric Rignot, a scientist at NASA’s Jet Propulsion Laboratory who has measured a doubling in ice loss from Greenland over the past decade, says: “We see things today that five years ago would have seemed completely impossible, extravagant, exaggerated.”

The fate of many mountain glaciers is already sealed.
(June 2007 issue)

World growth spurs faster climate change: report

Michael Perry, Reuters via Scientific American
..Emissions from burning fossil fuels have increased about 3 percent a year since 2000, up from 1 percent a year during the 1990s, said Australia’s peak scientific body, the Commonwealth Scientific and Industrial Research Organization (CSIRO).

“A major driver of the accelerating growth rate in emissions is that, globally, we’re burning more carbon per dollar of wealth created,” CSIRO scientist Mike Raupach said in a statement.
(22 May 2007)

Global and regional drivers of accelerating CO2 emissions

Various, Proceedings of the National Academy of Sciences
CO2 emissions from fossil-fuel burning and industrial processes have been accelerating at a global scale, with their growth rate increasing from 1.1% y-1 for 1990-1999 to >3% y-1 for 2000-2004.

The emissions growth rate since 2000 was greater than for the most fossil-fuel intensive of the Intergovernmental Panel on Climate Change emissions scenarios developed in the late 1990s. Global emissions growth since 2000 was driven by a cessation or reversal of earlier declining trends in the energy intensity of gross domestic product (GDP) (energy/GDP) and the carbon intensity of energy (emissions/energy), coupled with continuing increases in population and per-capita GDP.

Nearly constant or slightly increasing trends in the carbon intensity of energy have been recently observed in both developed and developing regions. No region is decarbonizing its energy supply.

The growth rate in emissions is strongest in rapidly developing economies, particularly China. Together, the developing and least-developed economies (forming 80% of the world’s population) accounted for 73% of global emissions growth in 2004 but only 41% of global emissions and only 23% of global cumulative emissions since the mid-18th century.

The results have implications for global equity.
(22 May 2007)
Contributor SP writes:The links take you to the publishers abstract page from where you can get the .pdf and any supporting information.

Irreducible imprecision in atmospheric and oceanic simulations

James C. McWilliams, Proceedings of the National Academy of Sciences
Atmospheric and oceanic computational simulation models often successfully depict chaotic space-time patterns, flow phenomena, dynamical balances, and equilibrium distributions that mimic nature.

This success is accomplished through necessary but nonunique choices for discrete algorithms, parameterizations, and coupled contributing processes that introduce structural instability into the model.

Therefore, we should expect a degree of irreducible imprecision in quantitative correspondences with nature, even with plausibly formulated models and careful calibration (tuning) to several empirical measures. Where precision is an issue (e.g., in a climate forecast), only simulation ensembles made across systematically designed model families allow an estimate of the level of relevant irreducible imprecision.
(22 May 2007)
Contributor SP writes:
The links take you to the publishers abstract page from where you can get the .pdf and any supporting information.